Case Study
BASF
Project overview
- 122,000 employees.
- R&D centers in 20+ countries.
- $ 65 billion in annual revenue.
Global deployment of visual intelligence for agricultural research.
Each year, BASF conducts several thousands of research trials in agricultural stations worldwide to measure product performance under different field conditions. Collecting such a high quantity of data means that there is a need for streamlined backend solutions so that BASF can realize the full potential of their visual drone data. Partnering with Alteia, BASF's agricultural research stations use the Alteia platform to streamline and standardize sensor-based field studies data. This allows them to turn visual drone data into actionable insights and, ultimately, new sustainable solutions for the agricultural market.
For example, thoroughly understanding the observed crops, their surroundings, and how they respond to environmental conditions can reduce the time to market for new products. In addition, working on a single cloud platform allows field agronomists to automatically vectorize and geo-reference microplots and generate biological data and crop behavior per plot.
For example, thoroughly understanding the observed crops, their surroundings, and how they respond to environmental conditions can reduce the time to market for new products. In addition, working on a single cloud platform allows field agronomists to automatically vectorize and geo-reference microplots and generate biological data and crop behavior per plot.
Results
90%
less time spent in data processing
30%
reduction in time to market for new products
20+
countries worldwide
Alteia Platform
Leverage Alteia's visual intelligence toolkit for use-cases specific to your activities.
Project highlights
- Automate and optimize field data collection.
- Accumulate real-time insights into how plants respond to environmental conditions.
- Build digital twins of research fields.
- Map and analyze hectares of plots across all trial sites.
- Collaborate on a single cloud platform.
- Generate insights into crop behavior based on environmental factors.